NVIDIA and Lilly launch $1B AI lab for drug discovery
NVIDIA and Eli Lilly are teaming up to push artificial intelligence deeper into drug discovery, announcing a joint AI co-innovation lab aimed at reinventing how medicines are discovered, developed and manufactured. The companies plan to invest up to $1 billion over five years in talent, infrastructure and compute to support the initiative.
For eeNews Europe readers, this announcement matters because it highlights how advanced AI infrastructure, accelerated computing and next-generation architectures are becoming central to life sciences. It also shows how platforms, robotics and “physical AI” are converging into large-scale industrial applications beyond traditional semiconductor markets.
AI infrastructure meets pharma science
The new lab, based in the San Francisco Bay Area, will co-locate Lilly experts in biology, chemistry and medicine with NVIDIA AI researchers and engineers. The goal is to generate massive, high-quality datasets and build powerful AI models that can dramatically shorten development cycles for new drugs.
The lab will be built on NVIDIA’s BioNeMo platform and will take advantage of future NVIDIA architectures, including Vera Rubin. According to the companies, the collaboration brings together Lilly’s drug discovery and manufacturing expertise with NVIDIA’s leadership in accelerated computing and AI infrastructure.
“AI is transforming every industry, and its most profound impact will be in life sciences,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA and Lilly are bringing together the best of our industries to invent a new blueprint for drug discovery — one where scientists can explore vast biological and chemical spaces in silico before a single molecule is made.”
Lilly CEO David A. Ricks emphasized the long-term ambition. “For nearly 150 years, we’ve been working to bring life-changing medicines to patients,” he said. “Combining our volumes of data and scientific knowledge with NVIDIA’s computational power and model-building expertise could reinvent drug discovery as we know it.”
Continuous learning, robotics and physical AI
A key focus of the collaboration is creating a “continuous learning system” that tightly links Lilly’s wet labs with computational dry labs. This scientist-in-the-loop approach aims to enable 24/7 AI-assisted experimentation, where experiments, data generation and model development constantly feed back into one another.
The initiative also builds on Lilly’s previously announced AI supercomputer, described as the most powerful in the pharmaceutical industry. This AI factory will train large biomedical foundation and frontier models to identify and optimize molecules faster and more accurately, while also supporting applications in manufacturing, medical imaging and scientific AI agents.
Beyond discovery, the partners plan to explore AI in clinical development, manufacturing and commercial operations. Physical AI, robotics and digital twins are expected to play a role in scaling production and strengthening supply chains. Using NVIDIA Omniverse and RTX PRO Servers, Lilly plans to model and optimize manufacturing lines before making real-world changes.
The co-innovation lab is expected to begin operations in South San Francisco early this year, signaling another step in the growing overlap between advanced computing platforms and the life sciences industry.
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